Instructions to use error577/4e03c89a-8b75-498e-b418-baeb044e5bd5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use error577/4e03c89a-8b75-498e-b418-baeb044e5bd5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "error577/4e03c89a-8b75-498e-b418-baeb044e5bd5") - Notebooks
- Google Colab
- Kaggle
File size: 4,563 Bytes
4b6bcb8 ff7a719 4b6bcb8 ff7a719 4b6bcb8 ff7a719 4b6bcb8 ff7a719 4b6bcb8 ff7a719 4b6bcb8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 | ---
library_name: peft
base_model: peft-internal-testing/tiny-dummy-qwen2
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 4e03c89a-8b75-498e-b418-baeb044e5bd5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.1`
```yaml
adapter: qlora
base_model: peft-internal-testing/tiny-dummy-qwen2
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- cfeccc189e92571d_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/cfeccc189e92571d_train_data.json
type:
field_instruction: startphrase
field_output: gold-ending
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 200
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 64
gradient_checkpointing: true
group_by_length: true
hub_model_id: error577/4e03c89a-8b75-498e-b418-baeb044e5bd5
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.15
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: constant_with_warmup
micro_batch_size: 4
mlflow_experiment_name: /tmp/cfeccc189e92571d_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch_fused
output_dir: miner_id_24
pad_to_sequence_len: true
restore_best_weights: true
auto_resume_from_checkpoints: true
s2_attention: null
sample_packing: false
save_steps: 200
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.005
wandb_entity: null
wandb_mode: online
wandb_name: 85f02ab3-c5bc-4ce0-94a6-aae2ba376e08
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 85f02ab3-c5bc-4ce0-94a6-aae2ba376e08
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# 4e03c89a-8b75-498e-b418-baeb044e5bd5
This model is a fine-tuned version of [peft-internal-testing/tiny-dummy-qwen2](https://huggingface.co/peft-internal-testing/tiny-dummy-qwen2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 11.8905
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 11.9295 | 0.0003 | 1 | 11.9293 |
| 11.8831 | 0.0695 | 200 | 11.8963 |
| 11.8873 | 0.1390 | 400 | 11.8939 |
| 11.8841 | 0.2085 | 600 | 11.8926 |
| 11.8756 | 0.2780 | 800 | 11.8919 |
| 11.8757 | 0.3475 | 1000 | 11.8918 |
| 11.8828 | 0.4170 | 1200 | 11.8915 |
| 11.884 | 0.4865 | 1400 | 11.8916 |
| 11.8848 | 0.5560 | 1600 | 11.8913 |
| 11.8737 | 0.6255 | 1800 | 11.8904 |
| 11.8768 | 0.6950 | 2000 | 11.8906 |
| 11.8752 | 0.7645 | 2200 | 11.8906 |
| 11.8774 | 0.8340 | 2400 | 11.8901 |
| 11.8759 | 0.9035 | 2600 | 11.8900 |
| 11.8754 | 0.9730 | 2800 | 11.8900 |
| 11.8156 | 1.0425 | 3000 | 11.8901 |
| 11.7092 | 1.1120 | 3200 | 11.8905 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1 |